Comparison of different deep learning approaches for parotid gland segmentation from CT images. - Annika Hänsch; Michael Schwier; Tobias Gass; Tomasz Morgas; Benjamin Haas; Jan Klein 001; Horst K. Hahn (Computer-Aided Diagnosis, 2018)

Artifact-driven sampling schemes for robust female pelvis CBCT segmentation using deep learning. - Annika Hänsch; Volker Dicken; Jan Klein 001; Tomasz Morgas; Benjamin Haas; Horst K. Hahn (Computer-Aided Diagnosis, 2019)

Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation. - Annika Hänsch; Bastian Cheng; Benedikt Frey; Carola Mayer; Marvin Petersen; Iris Lettow; Farhad Yazdan Shenas; Götz Thomalla; Jan Klein 001; Horst K. Hahn (OR/MLCN@MICCAI, 2019)

Quantitative and qualitative methods for efficient evaluation of multiple 3D organ segmentations. - Volker Dicken; Annika Hänsch; Jan Hendrik Moltz; Benjamin Haas; Thomas Coradi; Tomasz Morgas; Jan Klein 001 (Image Processing, 2019)

Learning a Loss Function for Segmentation: A Feasibility Study. - Jan Hendrik Moltz; Annika Hänsch; Bianca Lassen-Schmidt; Benjamin Haas; A. Genghi; J. Schreier; Tomasz Morgas; Jan Klein 001 (ISBI, 2020)

Implications of Dataset Heterogeneity on Deep Learning Performance in Medical Image Segmentation - Annika Hänsch (2021)

Robust Liver Segmentation with Deep Learning Across DCE-MRI Contrast Phases. - Annika Hänsch; Felix Thielke; Hans Meine; Shereen Rennebaum; Matthias F. Froelich; Lena S. Becker; Jan B. Hinrichs; Andrea Schenk (Bildverarbeitung für die Medizin, 2022)

Iterative Method to Register Longitudinal MRI Acquisitions in Neurosurgical Context. - Luca Canalini; Jan Klein 001; Annika Gerken; Stefan Heldmann; Alessa Hering; Horst K. Hahn (BrainLes@MICCAI, 2022)

Deep learning-assisted fully automatic fiber tracking for tremor treatment. - Annika Hänsch; Jürgen W. Jenne; Neeraj Upadhyay; Carsten Schmeel; Veronika Purrer; Ullrich Wüllner; Jan Klein 001 (Image-Guided Procedures, 2022)

Improving deep learning based liver vessel segmentation using automated connectivity analysis. - Felix Thielke; Farina Kock; Annika Hänsch; Joachim Georgii; Nasreddin Abolmaali; Itaru Endo; Hans Meine; Andrea Schenk (Image Processing, 2022)

AI-Based Detection of Aspiration for Video-Endoscopy with Visual Aids in Meaningful Frames to Interpret the Model Outcome. - Jürgen Konradi; Milla Zajber; Ulrich Betz; Philipp Drees; Annika Gerken; Hans Meine (Sensors, 2022)

CNN-based Whole Breast Segmentation in Longitudinal High-risk MRI Study - Initial Findings on Quality vs. Quantity of Training Annotations. - Ani Ambroladze; Horst K. Hahn; Heba Amer; Michael Ingrisch; Annika Gerken; Markus T. Wenzel; Michael Püsken; Andreas Mittermeier; Christoph Engel; Rita Schmutzler; Eva M. Fallenberg (Bildverarbeitung für die Medizin, 2023)

Abstract: Liver Tumor Segmentation in Late-phase MRI using Multi-model Training and an Anisotropic U-Net. - Annika Gerken; Grzegorz Chlebus; Hans Meine; Felix Thielke; Farina Kock; Tobias Paulus; Nasreddin Abolmaali; Andrea Schenk (Bildverarbeitung für die Medizin, 2023)

Combining arterial and venous CT scans in a multi-encoder network for improved hepatic vessel segmentation. - Felix Thielke; Farina Kock; Annika Hänsch; Nasreddin Abolmaali; Andrea Schenk; Hans Meine (Image Processing, 2023)

Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow. - Alessa Hering; Max Westphal; Annika Gerken; Haidara Almansour; Michael Maurer; Benjamin P. Geisler; Temke Kohlbrandt; Thomas Eigentler; Teresa Amaral; Nikolas Lessmann; Sergios Gatidis; Horst K. Hahn; et al. (Int. J. Comput. Assist. Radiol. Surg., 2024)